现已上线！2025 年 Telegram 研究 — 年度关键洞察 
Machine Learning
前往频道在 Telegram
Real Machine Learning — simple, practical, and built on experience. Learn step by step with clear explanations and working code. Admin: @HusseinSheikho || @Hussein_Sheikho
显示更多📈 Telegram 频道 Machine Learning 的分析概览
频道 Machine Learning (@machinelearning9) 英语 语言赛道中的 是活跃参与者。目前社区聚集了 40 208 名订阅者，在 技术与应用 类别中位列第 3 344，并在 叙利亚 地区排名第 228 位。
📊 受众指标与增长动态
自 невідомо 创建以来，项目保持高速增长，吸引了 40 208 名订阅者。
根据 03 七月, 2026 的最新数据，频道保持稳定运转。过去 30 天订阅人数变化为 338，过去 24 小时变化为 9，整体触达仍然可观。
- 认证状态： 未认证
- 互动率 (ER)： 平均受众互动率为 2.04%。内容发布后 24 小时内通常能获得 2.42% 的反应，占订阅者总量。
- 帖子覆盖： 每篇帖子平均可获得 822 次浏览，首日通常累积 973 次浏览。
- 互动与反馈： 受众积极参与，单帖平均反应数为 3。
- 主题关注点： 内容集中在 distance, insidead, gpu, learning, degree 等核心主题上。
📝 描述与内容策略
作者将该频道定位为表达主观观点的平台：
“Real Machine Learning — simple, practical, and built on experience.
Learn step by step with clear explanations and working code.
Admin: @HusseinSheikho || @Hussein_Sheikho”
凭借高频更新（最新数据采集于 04 七月, 2026），频道始终保持新鲜度与高覆盖。分析显示受众积极互动，使其成为 技术与应用 类别中的关键影响点。
40 208
订阅者
+924 小时
+727 天
+33830 天
帖子存档
40 215
📌 Understanding KL Divergence, Entropy, and Related Concepts
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-08 | ⏱️ Read time: 8 min read
Important concepts in information theory, machine learning, and statistics
40 215
📌 Nine Rules for Running Rust in the Browser
🗂 Category: PROGRAMMING
🕒 Date: 2024-10-08 | ⏱️ Read time: 25 min read
Practical lessons from porting range-set-blaze to WASM
40 215
📌 Graph Neural Networks Part 2. Graph Attention Networks vs. GCNs
🗂 Category:
🕒 Date: 2024-10-08 | ⏱️ Read time: 9 min read
A model that pays attention to your graph
40 215
📌 Still Manually Reviewing All User Interactions For Your AI Solutions?
🗂 Category: BUSINESS
🕒 Date: 2024-10-08 | ⏱️ Read time: 7 min read
Discover how to use cosine similarity to save hours and streamline your AI systems
40 215
📌 TDS Newsletter: To Better Understand AI, Look Under the Hood
🗂 Category: THE VARIABLE
🕒 Date: 2025-09-25 | ⏱️ Read time: 3 min read
AI-powered tools tend to generate extreme reactions: on one side we have the “It’s magic!” and…
40 215
📌 Make the Switch from Software Engineer to ML Engineer
🗂 Category: CAREER ADVICE
🕒 Date: 2024-10-08 | ⏱️ Read time: 9 min read
7 steps that helped me transition from a software engineer to Machine Learning engineer
40 215
📌 How to Improve Model Quality Without Building Larger Models
🗂 Category:
🕒 Date: 2024-10-08 | ⏱️ Read time: 12 min read
Going into the Google DeepMind’s “Scaling LLM Test-Time Compute Optimally can be More Effective than…
40 215
📌 A Deeper Dive into Odds Ratios Using Logistic Regression
🗂 Category: STATISTICS
🕒 Date: 2024-10-08 | ⏱️ Read time: 21 min read
A comprehensive guide on how to extract and explore odds ratios from a Logistic Regression…
40 215
📌 From Set Transformer to Perceiver Sampler
🗂 Category: DEEP LEARNING
🕒 Date: 2024-10-08 | ⏱️ Read time: 4 min read
On multi-modal LLM Flamingo’s vision encoder
40 215
📌 ITT vs LATE: Estimating Causal Effects with IV in Experiments with Imperfect Compliance
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-09 | ⏱️ Read time: 11 min read
Intuition, step-by-step script, and assumptions needed for the use of IV
40 215
📌 Embracing Uncertainty: The Power of Fuzzy Logic in Decision-Making
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-09 | ⏱️ Read time: 13 min read
Exploring how fuzzy logic enhances AI, systems thinking, and real-world applications
40 215
📌 5 AI Projects You Can Build This Weekend (with Python)
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-09 | ⏱️ Read time: 8 min read
From beginner-friendly to advanced
40 215
📌 From Newton to LLM’s
🗂 Category: PHYSICS
🕒 Date: 2024-10-09 | ⏱️ Read time: 17 min read
A new approach to AI reasoning optimization
40 215
📌 Mathematics I Look for in Data Scientist Interviews
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-09 | ⏱️ Read time: 18 min read
Let’s rebuild our data science foundation.
40 215
📌 Keep the Gradients Flowing
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-09 | ⏱️ Read time: 27 min read
Optimizing Sparse Neural Networks: Understanding Gradient Flow for Faster Training, and Better Performance in Deep…
40 215
📌 Mastering Sample Size Calculations
🗂 Category:
🕒 Date: 2024-10-09 | ⏱️ Read time: 19 min read
A/B Testing, Reject Inference, and How to Get the Right Sample Size for Your Experiments
40 215
📌 The Easiest Way to Learn and Use Python Today
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-09 | ⏱️ Read time: 9 min read
Google Colab and its integrated Generative AI, a powerful combination
40 215
📌 The Most Valuable LLM Dev Skill is Easy to Learn, But Costly to Practice.
🗂 Category: DATA SCIENCE
🕒 Date: 2024-10-09 | ⏱️ Read time: 18 min read
Here’s how not to waste your budget on evaluating models and systems.
40 215
📌 Fine-Tune Llama 3.2 for Powerful Performance on Targeted Tasks
🗂 Category: MACHINE LEARNING
🕒 Date: 2024-10-10 | ⏱️ Read time: 13 min read
Learn how you can fine-tune Llama3.2, Meta’s most recent Large language model, to achieve powerful…
40 215
📌 Forecasting with NHiTs: Uniting Deep Learning + Signal Processing Theory for Superior Accuracy
🗂 Category: ARTIFICIAL INTELLIGENCE
🕒 Date: 2024-10-10 | ⏱️ Read time: 12 min read
A high-performance DL model for all forecasting cases
